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Record W1768231395 · doi:10.1111/jpc.12101

Refugee children: Rights and wrongs

2013· article· en· W1768231395 on OpenAlexaboutno aff
Karen Zwi, Gervase Chaney

Bibliographic record

VenueJournal of Paediatrics and Child Health · 2013
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeMedicinePersecutionPublic healthInternally displaced personDisplaced personEconomic growthSocioeconomicsPolitical sciencePoliticsLawSociologyNursing

Abstract

fetched live from OpenAlex

Over the last 30 years, there have been 'waves' of people who have arrived by boat in Australia in response to humanitarian crisis.These include the 1976-1981 arrivals mainly from Vietnam; the 1989-1998 arrivals mainly from Cambodia, Vietnam and Southern China; the 1999-2001 arrivals mainly from Afghanistan and Iraq.Note 2: Special Assistance Category refers to visa subclasses Emergency Rescue (where there are urgent and compelling reasons for resettlement) and Woman at Risk (for women living outside their home country where they are subject to persecution, without the protection of a male relative and in danger of gender-based victimisation, harassment or serious abuse)., Onshore; , Special Assistance Category; , Offshore special humanitarian; , Refugee.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0100.017
Scholarly communication0.0050.007
Open science0.0010.011
Research integrity0.0050.011
Insufficient payload (model declined to judge)0.0190.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.285
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2013
Admission routes1
Has abstractyes

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